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Updated: Jul 6, 2025

Non-invasive Imaging of Acute Allograft Rejection after Rat Renal Transplantation Using 18F-FDG PET
Published on: April 28, 2013
Potential and Uncertainties of RejectClass in Acute Kidney Graft Dysfunction: An Independent Validation Study
Friedrich A von Samson-Himmelstjerna1, Nassim Kakavand1, Charlotte Gleske2
1Department of Nephrology and Hypertension, University Hospital Schleswig-Holstein-Campus Kiel, Kiel, Germany.
Background:
Kidney graft rejections are classified based on the Banff classification. The RejectClass algorithm, initially derived from a cohort comprising mostly protocol biopsies, identifies data-driven phenotypes of acute rejection and chronic pathology using Banff lesion scores. It also provides composite scores for inflammation activity and chronicity. This study independently evaluates the performance of RejectClass in a cohort consisting entirely of indication biopsies.
Methods:
We retrospectively applied RejectClass to 441 patients from the German TRABIO (TRAnsplant BIOpsies) cohort who had received indication biopsies. The primary endpoint was death-censored graft failure during 2 y of follow-up.
Results:
The application of RejectClass to our cohort demonstrated moderately comparable phenotypic features with the derivation cohort, and most clusters indicated an elevated risk of graft loss. However, the reproduction of all phenotypes and the associated risks of graft failure, as depicted in the original studies, was not fully accomplished. In contrast, adjusted Cox proportional hazards analyses substantiated that both the inflammation score and the chronicity score are independently associated with graft loss, exhibiting hazard ratios of 1.7 (95% confidence interval, 1.2-2.3; P = 0.002) and 2.2 (95% confidence interval, 1.8-2.6; P < 0.001), respectively, per 0.25-point increment (scale: 0.0-1.0).
Conclusions:
The composite inflammation and chronicity scores may already have direct utility in quantitatively assessing the disease stage. Further refinement and validation of RejectClass clusters are necessary to achieve more reliable and accurate phenotyping of rejection.
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